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run_imagenet_all.sh
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run_imagenet_all.sh
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#!/bin/bash
# AlexNet
# Acc@1: 56.522, Acc@5: 79.066, Params: 61.1M, GFLOPS: 0.71
python train_feature_density_estimator.py "checkpoint/Flow_AlexNet.pt" "AlexNet" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_AlexNet.pt" "AlexNet" "results/imagenet_results.csv"
# ConvNeXt_Base
# Acc@1: 84.062, Acc@5: 96.87, Params: 88.6M, GFLOPS: 15.36
python train_feature_density_estimator.py "checkpoint/Flow_ConvNeXt_Base.pt" "ConvNeXt_Base" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ConvNeXt_Base.pt" "ConvNeXt_Base" "results/imagenet_results.csv"
# ConvNeXt_Large
# Acc@1: 84.414, Acc@5: 96.976, Params: 197.8M, GFLOPS: 34.36
python train_feature_density_estimator.py "checkpoint/Flow_ConvNeXt_Large.pt" "ConvNeXt_Large" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ConvNeXt_Large.pt" "ConvNeXt_Large" "results/imagenet_results.csv"
# ConvNeXt_Small
# Acc@1: 83.616, Acc@5: 96.65, Params: 50.2M, GFLOPS: 8.68
python train_feature_density_estimator.py "checkpoint/Flow_ConvNeXt_Small.pt" "ConvNeXt_Small" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ConvNeXt_Small.pt" "ConvNeXt_Small" "results/imagenet_results.csv"
# ConvNeXt_Tiny
# Acc@1: 82.52, Acc@5: 96.146, Params: 28.6M, GFLOPS: 4.46
python train_feature_density_estimator.py "checkpoint/Flow_ConvNeXt_Tiny.pt" "ConvNeXt_Tiny" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ConvNeXt_Tiny.pt" "ConvNeXt_Tiny" "results/imagenet_results.csv"
# DenseNet121
# Acc@1: 74.434, Acc@5: 91.972, Params: 8.0M, GFLOPS: 2.83
python train_feature_density_estimator.py "checkpoint/Flow_DenseNet121.pt" "DenseNet121" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_DenseNet121.pt" "DenseNet121" "results/imagenet_results.csv"
# DenseNet161
# Acc@1: 77.138, Acc@5: 93.56, Params: 28.7M, GFLOPS: 7.73
python train_feature_density_estimator.py "checkpoint/Flow_DenseNet161.pt" "DenseNet161" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_DenseNet161.pt" "DenseNet161" "results/imagenet_results.csv"
# DenseNet169
# Acc@1: 75.6, Acc@5: 92.806, Params: 14.1M, GFLOPS: 3.36
python train_feature_density_estimator.py "checkpoint/Flow_DenseNet169.pt" "DenseNet169" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_DenseNet169.pt" "DenseNet169" "results/imagenet_results.csv"
# DenseNet201
# Acc@1: 76.896, Acc@5: 93.37, Params: 20.0M, GFLOPS: 4.29
python train_feature_density_estimator.py "checkpoint/Flow_DenseNet201.pt" "DenseNet201" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_DenseNet201.pt" "DenseNet201" "results/imagenet_results.csv"
# EfficientNet_B0
# Acc@1: 77.692, Acc@5: 93.532, Params: 5.3M, GFLOPS: 0.39
python train_feature_density_estimator.py "checkpoint/Flow_EfficientNet_B0.pt" "EfficientNet_B0" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_EfficientNet_B0.pt" "EfficientNet_B0" "results/imagenet_results.csv"
# EfficientNet_B1_V1
# Acc@1: 78.642, Acc@5: 94.186, Params: 7.8M, GFLOPS: 0.69
python train_feature_density_estimator.py "checkpoint/Flow_EfficientNet_B1_V1.pt" "EfficientNet_B1_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_EfficientNet_B1_V1.pt" "EfficientNet_B1_V1" "results/imagenet_results.csv"
# EfficientNet_B1_V2
# Acc@1: 79.838, Acc@5: 94.934, Params: 7.8M, GFLOPS: 0.69
python train_feature_density_estimator.py "checkpoint/Flow_EfficientNet_B1_V2.pt" "EfficientNet_B1_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_EfficientNet_B1_V2.pt" "EfficientNet_B1_V2" "results/imagenet_results.csv"
# EfficientNet_B2
# Acc@1: 80.608, Acc@5: 95.31, Params: 9.1M, GFLOPS: 1.09
python train_feature_density_estimator.py "checkpoint/Flow_EfficientNet_B2.pt" "EfficientNet_B2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_EfficientNet_B2.pt" "EfficientNet_B2" "results/imagenet_results.csv"
# EfficientNet_B3
# Acc@1: 82.008, Acc@5: 96.054, Params: 12.2M, GFLOPS: 1.83
python train_feature_density_estimator.py "checkpoint/Flow_EfficientNet_B3.pt" "EfficientNet_B3" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_EfficientNet_B3.pt" "EfficientNet_B3" "results/imagenet_results.csv"
# EfficientNet_B4
# Acc@1: 83.384, Acc@5: 96.594, Params: 19.3M, GFLOPS: 4.39
python train_feature_density_estimator.py "checkpoint/Flow_EfficientNet_B4.pt" "EfficientNet_B4" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_EfficientNet_B4.pt" "EfficientNet_B4" "results/imagenet_results.csv"
# EfficientNet_B5
# Acc@1: 83.444, Acc@5: 96.628, Params: 30.4M, GFLOPS: 10.27
python train_feature_density_estimator.py "checkpoint/Flow_EfficientNet_B5.pt" "EfficientNet_B5" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_EfficientNet_B5.pt" "EfficientNet_B5" "results/imagenet_results.csv"
# EfficientNet_B6
# Acc@1: 84.008, Acc@5: 96.916, Params: 43.0M, GFLOPS: 19.07
python train_feature_density_estimator.py "checkpoint/Flow_EfficientNet_B6.pt" "EfficientNet_B6" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_EfficientNet_B6.pt" "EfficientNet_B6" "results/imagenet_results.csv"
# EfficientNet_B7
# Acc@1: 84.122, Acc@5: 96.908, Params: 66.3M, GFLOPS: 37.75
python train_feature_density_estimator.py "checkpoint/Flow_EfficientNet_B7.pt" "EfficientNet_B7" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_EfficientNet_B7.pt" "EfficientNet_B7" "results/imagenet_results.csv"
# EfficientNet_V2_L
# Acc@1: 85.808, Acc@5: 97.788, Params: 118.5M, GFLOPS: 56.08
python train_feature_density_estimator.py "checkpoint/Flow_EfficientNet_V2_L.pt" "EfficientNet_V2_L" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_EfficientNet_V2_L.pt" "EfficientNet_V2_L" "results/imagenet_results.csv"
# EfficientNet_V2_M
# Acc@1: 85.112, Acc@5: 97.156, Params: 54.1M, GFLOPS: 24.58
python train_feature_density_estimator.py "checkpoint/Flow_EfficientNet_V2_M.pt" "EfficientNet_V2_M" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_EfficientNet_V2_M.pt" "EfficientNet_V2_M" "results/imagenet_results.csv"
# EfficientNet_V2_S
# Acc@1: 84.228, Acc@5: 96.878, Params: 21.5M, GFLOPS: 8.37
python train_feature_density_estimator.py "checkpoint/Flow_EfficientNet_V2_S.pt" "EfficientNet_V2_S" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_EfficientNet_V2_S.pt" "EfficientNet_V2_S" "results/imagenet_results.csv"
# GoogLeNet
# Acc@1: 69.778, Acc@5: 89.53, Params: 6.6M, GFLOPS: 1.5
python train_feature_density_estimator.py "checkpoint/Flow_GoogLeNet.pt" "GoogLeNet" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_GoogLeNet.pt" "GoogLeNet" "results/imagenet_results.csv"
# Inception_V3
# Acc@1: 77.294, Acc@5: 93.45, Params: 27.2M, GFLOPS: 5.71
python train_feature_density_estimator.py "checkpoint/Flow_Inception_V3.pt" "Inception_V3" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_Inception_V3.pt" "Inception_V3" "results/imagenet_results.csv"
# MNASNet0_5
# Acc@1: 67.734, Acc@5: 87.49, Params: 2.2M, GFLOPS: 0.1
python train_feature_density_estimator.py "checkpoint/Flow_MNASNet0_5.pt" "MNASNet0_5" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_MNASNet0_5.pt" "MNASNet0_5" "results/imagenet_results.csv"
# MNASNet0_75
# Acc@1: 71.18, Acc@5: 90.496, Params: 3.2M, GFLOPS: 0.21
python train_feature_density_estimator.py "checkpoint/Flow_MNASNet0_75.pt" "MNASNet0_75" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_MNASNet0_75.pt" "MNASNet0_75" "results/imagenet_results.csv"
# MNASNet1_0
# Acc@1: 73.456, Acc@5: 91.51, Params: 4.4M, GFLOPS: 0.31
python train_feature_density_estimator.py "checkpoint/Flow_MNASNet1_0.pt" "MNASNet1_0" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_MNASNet1_0.pt" "MNASNet1_0" "results/imagenet_results.csv"
# MNASNet1_3
# Acc@1: 76.506, Acc@5: 93.522, Params: 6.3M, GFLOPS: 0.53
python train_feature_density_estimator.py "checkpoint/Flow_MNASNet1_3.pt" "MNASNet1_3" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_MNASNet1_3.pt" "MNASNet1_3" "results/imagenet_results.csv"
# MaxVit_T
# Acc@1: 83.7, Acc@5: 96.722, Params: 30.9M, GFLOPS: 5.56
python train_feature_density_estimator.py "checkpoint/Flow_MaxVit_T.pt" "MaxVit_T" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_MaxVit_T.pt" "MaxVit_T" "results/imagenet_results.csv"
# MobileNet_V2_V1
# Acc@1: 71.878, Acc@5: 90.286, Params: 3.5M, GFLOPS: 0.3
python train_feature_density_estimator.py "checkpoint/Flow_MobileNet_V2_V1.pt" "MobileNet_V2_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_MobileNet_V2_V1.pt" "MobileNet_V2_V1" "results/imagenet_results.csv"
# MobileNet_V2_V2
# Acc@1: 72.154, Acc@5: 90.822, Params: 3.5M, GFLOPS: 0.3
python train_feature_density_estimator.py "checkpoint/Flow_MobileNet_V2_V2.pt" "MobileNet_V2_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_MobileNet_V2_V2.pt" "MobileNet_V2_V2" "results/imagenet_results.csv"
# MobileNet_V3_Large_V1
# Acc@1: 74.042, Acc@5: 91.34, Params: 5.5M, GFLOPS: 0.22
python train_feature_density_estimator.py "checkpoint/Flow_MobileNet_V3_Large_V1.pt" "MobileNet_V3_Large_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_MobileNet_V3_Large_V1.pt" "MobileNet_V3_Large_V1" "results/imagenet_results.csv"
# MobileNet_V3_Large_V2
# Acc@1: 75.274, Acc@5: 92.566, Params: 5.5M, GFLOPS: 0.22
python train_feature_density_estimator.py "checkpoint/Flow_MobileNet_V3_Large_V2.pt" "MobileNet_V3_Large_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_MobileNet_V3_Large_V2.pt" "MobileNet_V3_Large_V2" "results/imagenet_results.csv"
# MobileNet_V3_Small
# Acc@1: 67.668, Acc@5: 87.402, Params: 2.5M, GFLOPS: 0.06
python train_feature_density_estimator.py "checkpoint/Flow_MobileNet_V3_Small.pt" "MobileNet_V3_Small" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_MobileNet_V3_Small.pt" "MobileNet_V3_Small" "results/imagenet_results.csv"
# RegNet_X_16GF_V1
# Acc@1: 80.058, Acc@5: 94.944, Params: 54.3M, GFLOPS: 15.94
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_X_16GF_V1.pt" "RegNet_X_16GF_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_X_16GF_V1.pt" "RegNet_X_16GF_V1" "results/imagenet_results.csv"
# RegNet_X_16GF_V2
# Acc@1: 82.716, Acc@5: 96.196, Params: 54.3M, GFLOPS: 15.94
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_X_16GF_V2.pt" "RegNet_X_16GF_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_X_16GF_V2.pt" "RegNet_X_16GF_V2" "results/imagenet_results.csv"
# RegNet_X_1_6GF_V1
# Acc@1: 77.04, Acc@5: 93.44, Params: 9.2M, GFLOPS: 1.6
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_X_1_6GF_V1.pt" "RegNet_X_1_6GF_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_X_1_6GF_V1.pt" "RegNet_X_1_6GF_V1" "results/imagenet_results.csv"
# RegNet_X_1_6GF_V2
# Acc@1: 79.668, Acc@5: 94.922, Params: 9.2M, GFLOPS: 1.6
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_X_1_6GF_V2.pt" "RegNet_X_1_6GF_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_X_1_6GF_V2.pt" "RegNet_X_1_6GF_V2" "results/imagenet_results.csv"
# RegNet_X_32GF_V1
# Acc@1: 80.622, Acc@5: 95.248, Params: 107.8M, GFLOPS: 31.74
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_X_32GF_V1.pt" "RegNet_X_32GF_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_X_32GF_V1.pt" "RegNet_X_32GF_V1" "results/imagenet_results.csv"
# RegNet_X_32GF_V2
# Acc@1: 83.014, Acc@5: 96.288, Params: 107.8M, GFLOPS: 31.74
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_X_32GF_V2.pt" "RegNet_X_32GF_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_X_32GF_V2.pt" "RegNet_X_32GF_V2" "results/imagenet_results.csv"
# RegNet_X_3_2GF_V1
# Acc@1: 78.364, Acc@5: 93.992, Params: 15.3M, GFLOPS: 3.18
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_X_3_2GF_V1.pt" "RegNet_X_3_2GF_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_X_3_2GF_V1.pt" "RegNet_X_3_2GF_V1" "results/imagenet_results.csv"
# RegNet_X_3_2GF_V2
# Acc@1: 81.196, Acc@5: 95.43, Params: 15.3M, GFLOPS: 3.18
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_X_3_2GF_V2.pt" "RegNet_X_3_2GF_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_X_3_2GF_V2.pt" "RegNet_X_3_2GF_V2" "results/imagenet_results.csv"
# RegNet_X_400MF_V1
# Acc@1: 72.834, Acc@5: 90.95, Params: 5.5M, GFLOPS: 0.41
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_X_400MF_V1.pt" "RegNet_X_400MF_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_X_400MF_V1.pt" "RegNet_X_400MF_V1" "results/imagenet_results.csv"
# RegNet_X_400MF_V2
# Acc@1: 74.864, Acc@5: 92.322, Params: 5.5M, GFLOPS: 0.41
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_X_400MF_V2.pt" "RegNet_X_400MF_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_X_400MF_V2.pt" "RegNet_X_400MF_V2" "results/imagenet_results.csv"
# RegNet_X_800MF_V1
# Acc@1: 75.212, Acc@5: 92.348, Params: 7.3M, GFLOPS: 0.8
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_X_800MF_V1.pt" "RegNet_X_800MF_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_X_800MF_V1.pt" "RegNet_X_800MF_V1" "results/imagenet_results.csv"
# RegNet_X_800MF_V2
# Acc@1: 77.522, Acc@5: 93.826, Params: 7.3M, GFLOPS: 0.8
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_X_800MF_V2.pt" "RegNet_X_800MF_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_X_800MF_V2.pt" "RegNet_X_800MF_V2" "results/imagenet_results.csv"
# RegNet_X_8GF_V1
# Acc@1: 79.344, Acc@5: 94.686, Params: 39.6M, GFLOPS: 8
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_X_8GF_V1.pt" "RegNet_X_8GF_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_X_8GF_V1.pt" "RegNet_X_8GF_V1" "results/imagenet_results.csv"
# RegNet_X_8GF_V2
# Acc@1: 81.682, Acc@5: 95.678, Params: 39.6M, GFLOPS: 8
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_X_8GF_V2.pt" "RegNet_X_8GF_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_X_8GF_V2.pt" "RegNet_X_8GF_V2" "results/imagenet_results.csv"
# RegNet_Y_128GF_V1
# Acc@1: 88.228, Acc@5: 98.682, Params: 644.8M, GFLOPS: 374.57
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_128GF_V1.pt" "RegNet_Y_128GF_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_128GF_V1.pt" "RegNet_Y_128GF_V1" "results/imagenet_results.csv"
# RegNet_Y_128GF_V2
# Acc@1: 86.068, Acc@5: 97.844, Params: 644.8M, GFLOPS: 127.52
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_128GF_V2.pt" "RegNet_Y_128GF_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_128GF_V2.pt" "RegNet_Y_128GF_V2" "results/imagenet_results.csv"
# RegNet_Y_16GF_V1
# Acc@1: 80.424, Acc@5: 95.24, Params: 83.6M, GFLOPS: 15.91
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_16GF_V1.pt" "RegNet_Y_16GF_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_16GF_V1.pt" "RegNet_Y_16GF_V1" "results/imagenet_results.csv"
# RegNet_Y_16GF_V2
# Acc@1: 82.886, Acc@5: 96.328, Params: 83.6M, GFLOPS: 15.91
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_16GF_V2.pt" "RegNet_Y_16GF_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_16GF_V2.pt" "RegNet_Y_16GF_V2" "results/imagenet_results.csv"
# RegNet_Y_16GF_SWAG_E2E_V1
# Acc@1: 86.012, Acc@5: 98.054, Params: 83.6M, GFLOPS: 46.73
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_16GF_SWAG_E2E_V1.pt" "RegNet_Y_16GF_SWAG_E2E_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_16GF_SWAG_E2E_V1.pt" "RegNet_Y_16GF_SWAG_E2E_V1" "results/imagenet_results.csv"
# RegNet_Y_16GF_SWAG_LINEAR_V1
# Acc@1: 83.976, Acc@5: 97.244, Params: 83.6M, GFLOPS: 15.91
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_16GF_SWAG_LINEAR_V1.pt" "RegNet_Y_16GF_SWAG_LINEAR_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_16GF_SWAG_LINEAR_V1.pt" "RegNet_Y_16GF_SWAG_LINEAR_V1" "results/imagenet_results.csv"
# RegNet_Y_1_6GF_V1
# Acc@1: 77.95, Acc@5: 93.966, Params: 11.2M, GFLOPS: 1.61
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_1_6GF_V1.pt" "RegNet_Y_1_6GF_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_1_6GF_V1.pt" "RegNet_Y_1_6GF_V1" "results/imagenet_results.csv"
# RegNet_Y_1_6GF_V2
# Acc@1: 80.876, Acc@5: 95.444, Params: 11.2M, GFLOPS: 1.61
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_1_6GF_V2.pt" "RegNet_Y_1_6GF_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_1_6GF_V2.pt" "RegNet_Y_1_6GF_V2" "results/imagenet_results.csv"
# RegNet_Y_32GF_V1
# Acc@1: 80.878, Acc@5: 95.34, Params: 145.0M, GFLOPS: 32.28
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_32GF_V1.pt" "RegNet_Y_32GF_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_32GF_V1.pt" "RegNet_Y_32GF_V1" "results/imagenet_results.csv"
# RegNet_Y_32GF_V2
# Acc@1: 83.368, Acc@5: 96.498, Params: 145.0M, GFLOPS: 32.28
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_32GF_V2.pt" "RegNet_Y_32GF_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_32GF_V2.pt" "RegNet_Y_32GF_V2" "results/imagenet_results.csv"
# RegNet_Y_32GF_SWAG_E2E_V1
# Acc@1: 86.838, Acc@5: 98.362, Params: 145.0M, GFLOPS: 94.83
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_32GF_SWAG_E2E_V1.pt" "RegNet_Y_32GF_SWAG_E2E_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_32GF_SWAG_E2E_V1.pt" "RegNet_Y_32GF_SWAG_E2E_V1" "results/imagenet_results.csv"
# RegNet_Y_32GF_SWAG_LINEAR_V1
# Acc@1: 84.622, Acc@5: 97.48, Params: 145.0M, GFLOPS: 32.28
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_32GF_SWAG_LINEAR_V1.pt" "RegNet_Y_32GF_SWAG_LINEAR_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_32GF_SWAG_LINEAR_V1.pt" "RegNet_Y_32GF_SWAG_LINEAR_V1" "results/imagenet_results.csv"
# RegNet_Y_3_2GF_V1
# Acc@1: 78.948, Acc@5: 94.576, Params: 19.4M, GFLOPS: 3.18
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_3_2GF_V1.pt" "RegNet_Y_3_2GF_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_3_2GF_V1.pt" "RegNet_Y_3_2GF_V1" "results/imagenet_results.csv"
# RegNet_Y_3_2GF_V2
# Acc@1: 81.982, Acc@5: 95.972, Params: 19.4M, GFLOPS: 3.18
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_3_2GF_V2.pt" "RegNet_Y_3_2GF_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_3_2GF_V2.pt" "RegNet_Y_3_2GF_V2" "results/imagenet_results.csv"
# RegNet_Y_400MF_V1
# Acc@1: 74.046, Acc@5: 91.716, Params: 4.3M, GFLOPS: 0.4
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_400MF_V1.pt" "RegNet_Y_400MF_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_400MF_V1.pt" "RegNet_Y_400MF_V1" "results/imagenet_results.csv"
# RegNet_Y_400MF_V2
# Acc@1: 75.804, Acc@5: 92.742, Params: 4.3M, GFLOPS: 0.4
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_400MF_V2.pt" "RegNet_Y_400MF_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_400MF_V2.pt" "RegNet_Y_400MF_V2" "results/imagenet_results.csv"
# RegNet_Y_800MF_V1
# Acc@1: 76.42, Acc@5: 93.136, Params: 6.4M, GFLOPS: 0.83
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_800MF_V1.pt" "RegNet_Y_800MF_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_800MF_V1.pt" "RegNet_Y_800MF_V1" "results/imagenet_results.csv"
# RegNet_Y_800MF_V2
# Acc@1: 78.828, Acc@5: 94.502, Params: 6.4M, GFLOPS: 0.83
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_800MF_V2.pt" "RegNet_Y_800MF_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_800MF_V2.pt" "RegNet_Y_800MF_V2" "results/imagenet_results.csv"
# RegNet_Y_8GF_V1
# Acc@1: 80.032, Acc@5: 95.048, Params: 39.4M, GFLOPS: 8.47
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_8GF_V1.pt" "RegNet_Y_8GF_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_8GF_V1.pt" "RegNet_Y_8GF_V1" "results/imagenet_results.csv"
# RegNet_Y_8GF_V2
# Acc@1: 82.828, Acc@5: 96.33, Params: 39.4M, GFLOPS: 8.47
python train_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_8GF_V2.pt" "RegNet_Y_8GF_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_RegNet_Y_8GF_V2.pt" "RegNet_Y_8GF_V2" "results/imagenet_results.csv"
# ResNeXt101_32X8D_V1
# Acc@1: 79.312, Acc@5: 94.526, Params: 88.8M, GFLOPS: 16.41
python train_feature_density_estimator.py "checkpoint/Flow_ResNeXt101_32X8D_V1.pt" "ResNeXt101_32X8D_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ResNeXt101_32X8D_V1.pt" "ResNeXt101_32X8D_V1" "results/imagenet_results.csv"
# ResNeXt101_32X8D_V2
# Acc@1: 82.834, Acc@5: 96.228, Params: 88.8M, GFLOPS: 16.41
python train_feature_density_estimator.py "checkpoint/Flow_ResNeXt101_32X8D_V2.pt" "ResNeXt101_32X8D_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ResNeXt101_32X8D_V2.pt" "ResNeXt101_32X8D_V2" "results/imagenet_results.csv"
# ResNeXt101_64X4D
# Acc@1: 83.246, Acc@5: 96.454, Params: 83.5M, GFLOPS: 15.46
python train_feature_density_estimator.py "checkpoint/Flow_ResNeXt101_64X4D.pt" "ResNeXt101_64X4D" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ResNeXt101_64X4D.pt" "ResNeXt101_64X4D" "results/imagenet_results.csv"
# ResNeXt50_32X4D_V1
# Acc@1: 77.618, Acc@5: 93.698, Params: 25.0M, GFLOPS: 4.23
python train_feature_density_estimator.py "checkpoint/Flow_ResNeXt50_32X4D_V1.pt" "ResNeXt50_32X4D_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ResNeXt50_32X4D_V1.pt" "ResNeXt50_32X4D_V1" "results/imagenet_results.csv"
# ResNeXt50_32X4D_V2
# Acc@1: 81.198, Acc@5: 95.34, Params: 25.0M, GFLOPS: 4.23
python train_feature_density_estimator.py "checkpoint/Flow_ResNeXt50_32X4D_V2.pt" "ResNeXt50_32X4D_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ResNeXt50_32X4D_V2.pt" "ResNeXt50_32X4D_V2" "results/imagenet_results.csv"
# ResNet101_V1
# Acc@1: 77.374, Acc@5: 93.546, Params: 44.5M, GFLOPS: 7.8
python train_feature_density_estimator.py "checkpoint/Flow_ResNet101_V1.pt" "ResNet101_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ResNet101_V1.pt" "ResNet101_V1" "results/imagenet_results.csv"
# ResNet101_V2
# Acc@1: 81.886, Acc@5: 95.78, Params: 44.5M, GFLOPS: 7.8
python train_feature_density_estimator.py "checkpoint/Flow_ResNet101_V2.pt" "ResNet101_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ResNet101_V2.pt" "ResNet101_V2" "results/imagenet_results.csv"
# ResNet152_V1
# Acc@1: 78.312, Acc@5: 94.046, Params: 60.2M, GFLOPS: 11.51
python train_feature_density_estimator.py "checkpoint/Flow_ResNet152_V1.pt" "ResNet152_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ResNet152_V1.pt" "ResNet152_V1" "results/imagenet_results.csv"
# ResNet152_V2
# Acc@1: 82.284, Acc@5: 96.002, Params: 60.2M, GFLOPS: 11.51
python train_feature_density_estimator.py "checkpoint/Flow_ResNet152_V2.pt" "ResNet152_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ResNet152_V2.pt" "ResNet152_V2" "results/imagenet_results.csv"
# ResNet18
# Acc@1: 69.758, Acc@5: 89.078, Params: 11.7M, GFLOPS: 1.81
python train_feature_density_estimator.py "checkpoint/Flow_ResNet18.pt" "ResNet18" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ResNet18.pt" "ResNet18" "results/imagenet_results.csv"
# ResNet34
# Acc@1: 73.314, Acc@5: 91.42, Params: 21.8M, GFLOPS: 3.66
python train_feature_density_estimator.py "checkpoint/Flow_ResNet34.pt" "ResNet34" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ResNet34.pt" "ResNet34" "results/imagenet_results.csv"
# ResNet50_V1
# Acc@1: 76.13, Acc@5: 92.862, Params: 25.6M, GFLOPS: 4.09
python train_feature_density_estimator.py "checkpoint/Flow_ResNet50_V1.pt" "ResNet50_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ResNet50_V1.pt" "ResNet50_V1" "results/imagenet_results.csv"
# ResNet50_V2
# Acc@1: 80.858, Acc@5: 95.434, Params: 25.6M, GFLOPS: 4.09
python train_feature_density_estimator.py "checkpoint/Flow_ResNet50_V2.pt" "ResNet50_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ResNet50_V2.pt" "ResNet50_V2" "results/imagenet_results.csv"
# ShuffleNet_V2_X0_5
# Acc@1: 60.552, Acc@5: 81.746, Params: 1.4M, GFLOPS: 0.04
python train_feature_density_estimator.py "checkpoint/Flow_ShuffleNet_V2_X0_5.pt" "ShuffleNet_V2_X0_5" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ShuffleNet_V2_X0_5.pt" "ShuffleNet_V2_X0_5" "results/imagenet_results.csv"
# ShuffleNet_V2_X1_0
# Acc@1: 69.362, Acc@5: 88.316, Params: 2.3M, GFLOPS: 0.14
python train_feature_density_estimator.py "checkpoint/Flow_ShuffleNet_V2_X1_0.pt" "ShuffleNet_V2_X1_0" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ShuffleNet_V2_X1_0.pt" "ShuffleNet_V2_X1_0" "results/imagenet_results.csv"
# ShuffleNet_V2_X1_5
# Acc@1: 72.996, Acc@5: 91.086, Params: 3.5M, GFLOPS: 0.3
python train_feature_density_estimator.py "checkpoint/Flow_ShuffleNet_V2_X1_5.pt" "ShuffleNet_V2_X1_5" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ShuffleNet_V2_X1_5.pt" "ShuffleNet_V2_X1_5" "results/imagenet_results.csv"
# ShuffleNet_V2_X2_0
# Acc@1: 76.23, Acc@5: 93.006, Params: 7.4M, GFLOPS: 0.58
python train_feature_density_estimator.py "checkpoint/Flow_ShuffleNet_V2_X2_0.pt" "ShuffleNet_V2_X2_0" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ShuffleNet_V2_X2_0.pt" "ShuffleNet_V2_X2_0" "results/imagenet_results.csv"
# SqueezeNet1_0
# Acc@1: 58.092, Acc@5: 80.42, Params: 1.2M, GFLOPS: 0.82
python train_feature_density_estimator.py "checkpoint/Flow_SqueezeNet1_0.pt" "SqueezeNet1_0" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_SqueezeNet1_0.pt" "SqueezeNet1_0" "results/imagenet_results.csv"
# SqueezeNet1_1
# Acc@1: 58.178, Acc@5: 80.624, Params: 1.2M, GFLOPS: 0.35
python train_feature_density_estimator.py "checkpoint/Flow_SqueezeNet1_1.pt" "SqueezeNet1_1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_SqueezeNet1_1.pt" "SqueezeNet1_1" "results/imagenet_results.csv"
# Swin_B
# Acc@1: 83.582, Acc@5: 96.64, Params: 87.8M, GFLOPS: 15.43
python train_feature_density_estimator.py "checkpoint/Flow_Swin_B.pt" "Swin_B" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_Swin_B.pt" "Swin_B" "results/imagenet_results.csv"
# Swin_S
# Acc@1: 83.196, Acc@5: 96.36, Params: 49.6M, GFLOPS: 8.74
python train_feature_density_estimator.py "checkpoint/Flow_Swin_S.pt" "Swin_S" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_Swin_S.pt" "Swin_S" "results/imagenet_results.csv"
# Swin_T
# Acc@1: 81.474, Acc@5: 95.776, Params: 28.3M, GFLOPS: 4.49
python train_feature_density_estimator.py "checkpoint/Flow_Swin_T.pt" "Swin_T" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_Swin_T.pt" "Swin_T" "results/imagenet_results.csv"
# Swin_V2_B
# Acc@1: 84.112, Acc@5: 96.864, Params: 87.9M, GFLOPS: 20.32
python train_feature_density_estimator.py "checkpoint/Flow_Swin_V2_B.pt" "Swin_V2_B" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_Swin_V2_B.pt" "Swin_V2_B" "results/imagenet_results.csv"
# Swin_V2_S
# Acc@1: 83.712, Acc@5: 96.816, Params: 49.7M, GFLOPS: 11.55
python train_feature_density_estimator.py "checkpoint/Flow_Swin_V2_S.pt" "Swin_V2_S" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_Swin_V2_S.pt" "Swin_V2_S" "results/imagenet_results.csv"
# Swin_V2_T
# Acc@1: 82.072, Acc@5: 96.132, Params: 28.4M, GFLOPS: 5.94
python train_feature_density_estimator.py "checkpoint/Flow_Swin_V2_T.pt" "Swin_V2_T" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_Swin_V2_T.pt" "Swin_V2_T" "results/imagenet_results.csv"
# VGG11_BN
# Acc@1: 70.37, Acc@5: 89.81, Params: 132.9M, GFLOPS: 7.61
python train_feature_density_estimator.py "checkpoint/Flow_VGG11_BN.pt" "VGG11_BN" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_VGG11_BN.pt" "VGG11_BN" "results/imagenet_results.csv"
# VGG11
# Acc@1: 69.02, Acc@5: 88.628, Params: 132.9M, GFLOPS: 7.61
python train_feature_density_estimator.py "checkpoint/Flow_VGG11.pt" "VGG11" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_VGG11.pt" "VGG11" "results/imagenet_results.csv"
# VGG13_BN
# Acc@1: 71.586, Acc@5: 90.374, Params: 133.1M, GFLOPS: 11.31
python train_feature_density_estimator.py "checkpoint/Flow_VGG13_BN.pt" "VGG13_BN" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_VGG13_BN.pt" "VGG13_BN" "results/imagenet_results.csv"
# VGG13
# Acc@1: 69.928, Acc@5: 89.246, Params: 133.0M, GFLOPS: 11.31
python train_feature_density_estimator.py "checkpoint/Flow_VGG13.pt" "VGG13" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_VGG13.pt" "VGG13" "results/imagenet_results.csv"
# VGG16_BN
# Acc@1: 73.36, Acc@5: 91.516, Params: 138.4M, GFLOPS: 15.47
python train_feature_density_estimator.py "checkpoint/Flow_VGG16_BN.pt" "VGG16_BN" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_VGG16_BN.pt" "VGG16_BN" "results/imagenet_results.csv"
# VGG16_V1
# Acc@1: 71.592, Acc@5: 90.382, Params: 138.4M, GFLOPS: 15.47
python train_feature_density_estimator.py "checkpoint/Flow_VGG16_V1.pt" "VGG16_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_VGG16_V1.pt" "VGG16_V1" "results/imagenet_results.csv"
# VGG16_FEATURES
# Acc@1: nan nan, Acc@5: 138.4M, Params: 15.47, GFLOPS: Acc@1: 74.218, Acc@5: 91.842, Params: 143.7M,
python train_feature_density_estimator.py "checkpoint/Flow_VGG16_FEATURES.pt" "VGG16_FEATURES" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_VGG16_FEATURES.pt" "VGG16_FEATURES" "results/imagenet_results.csv"
# VGG19_BN
# GFLOPS: 19.63
python train_feature_density_estimator.py "checkpoint/Flow_VGG19_BN.pt" "VGG19_BN" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_VGG19_BN.pt" "VGG19_BN" "results/imagenet_results.csv"
# VGG19
# Acc@1: 72.376, Acc@5: 90.876, Params: 143.7M, GFLOPS: 19.63
python train_feature_density_estimator.py "checkpoint/Flow_VGG19.pt" "VGG19" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_VGG19.pt" "VGG19" "results/imagenet_results.csv"
# ViT_B_16_V1
# Acc@1: 81.072, Acc@5: 95.318, Params: 86.6M, GFLOPS: 17.56
python train_feature_density_estimator.py "checkpoint/Flow_ViT_B_16_V1.pt" "ViT_B_16_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ViT_B_16_V1.pt" "ViT_B_16_V1" "results/imagenet_results.csv"
# ViT_B_16_SWAG_E2E_V1
# Acc@1: 85.304, Acc@5: 97.65, Params: 86.9M, GFLOPS: 55.48
python train_feature_density_estimator.py "checkpoint/Flow_ViT_B_16_SWAG_E2E_V1.pt" "ViT_B_16_SWAG_E2E_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ViT_B_16_SWAG_E2E_V1.pt" "ViT_B_16_SWAG_E2E_V1" "results/imagenet_results.csv"
# ViT_B_16_SWAG_LINEAR_V1
# Acc@1: 81.886, Acc@5: 96.18, Params: 86.6M, GFLOPS: 17.56
python train_feature_density_estimator.py "checkpoint/Flow_ViT_B_16_SWAG_LINEAR_V1.pt" "ViT_B_16_SWAG_LINEAR_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ViT_B_16_SWAG_LINEAR_V1.pt" "ViT_B_16_SWAG_LINEAR_V1" "results/imagenet_results.csv"
# ViT_B_32
# Acc@1: 75.912, Acc@5: 92.466, Params: 88.2M, GFLOPS: 4.41
python train_feature_density_estimator.py "checkpoint/Flow_ViT_B_32.pt" "ViT_B_32" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ViT_B_32.pt" "ViT_B_32" "results/imagenet_results.csv"
# ViT_H_14_SWAG_E2E_V1
# Acc@1: 88.552, Acc@5: 98.694, Params: 633.5M, GFLOPS: 1016.72
python train_feature_density_estimator.py "checkpoint/Flow_ViT_H_14_SWAG_E2E_V1.pt" "ViT_H_14_SWAG_E2E_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ViT_H_14_SWAG_E2E_V1.pt" "ViT_H_14_SWAG_E2E_V1" "results/imagenet_results.csv"
# ViT_H_14_SWAG_LINEAR_V1
# Acc@1: 85.708, Acc@5: 97.73, Params: 632.0M, GFLOPS: 167.29
python train_feature_density_estimator.py "checkpoint/Flow_ViT_H_14_SWAG_LINEAR_V1.pt" "ViT_H_14_SWAG_LINEAR_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ViT_H_14_SWAG_LINEAR_V1.pt" "ViT_H_14_SWAG_LINEAR_V1" "results/imagenet_results.csv"
# ViT_L_16_V1
# Acc@1: 79.662, Acc@5: 94.638, Params: 304.3M, GFLOPS: 61.55
python train_feature_density_estimator.py "checkpoint/Flow_ViT_L_16_V1.pt" "ViT_L_16_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ViT_L_16_V1.pt" "ViT_L_16_V1" "results/imagenet_results.csv"
# ViT_L_16_SWAG_E2E_V1
# Acc@1: 88.064, Acc@5: 98.512, Params: 305.2M, GFLOPS: 361.99
python train_feature_density_estimator.py "checkpoint/Flow_ViT_L_16_SWAG_E2E_V1.pt" "ViT_L_16_SWAG_E2E_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ViT_L_16_SWAG_E2E_V1.pt" "ViT_L_16_SWAG_E2E_V1" "results/imagenet_results.csv"
# ViT_L_16_SWAG_LINEAR_V1
# Acc@1: 85.146, Acc@5: 97.422, Params: 304.3M, GFLOPS: 61.55
python train_feature_density_estimator.py "checkpoint/Flow_ViT_L_16_SWAG_LINEAR_V1.pt" "ViT_L_16_SWAG_LINEAR_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ViT_L_16_SWAG_LINEAR_V1.pt" "ViT_L_16_SWAG_LINEAR_V1" "results/imagenet_results.csv"
# ViT_L_32
# Acc@1: 76.972, Acc@5: 93.07, Params: 306.5M, GFLOPS: 15.38
python train_feature_density_estimator.py "checkpoint/Flow_ViT_L_32.pt" "ViT_L_32" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_ViT_L_32.pt" "ViT_L_32" "results/imagenet_results.csv"
# Wide_ResNet101_2_V1
# Acc@1: 78.848, Acc@5: 94.284, Params: 126.9M, GFLOPS: 22.75
python train_feature_density_estimator.py "checkpoint/Flow_Wide_ResNet101_2_V1.pt" "Wide_ResNet101_2_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_Wide_ResNet101_2_V1.pt" "Wide_ResNet101_2_V1" "results/imagenet_results.csv"
# Wide_ResNet101_2_V2
# Acc@1: 82.51, Acc@5: 96.02, Params: 126.9M, GFLOPS: 22.75
python train_feature_density_estimator.py "checkpoint/Flow_Wide_ResNet101_2_V2.pt" "Wide_ResNet101_2_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_Wide_ResNet101_2_V2.pt" "Wide_ResNet101_2_V2" "results/imagenet_results.csv"
# Wide_ResNet50_2_V1
# Acc@1: 78.468, Acc@5: 94.086, Params: 68.9M, GFLOPS: 11.4
python train_feature_density_estimator.py "checkpoint/Flow_Wide_ResNet50_2_V1.pt" "Wide_ResNet50_2_V1" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_Wide_ResNet50_2_V1.pt" "Wide_ResNet50_2_V1" "results/imagenet_results.csv"
# Wide_ResNet50_2_V2
# Acc@1: 81.602, Acc@5: 95.758, Params: 68.9M, GFLOPS: 11.4
python train_feature_density_estimator.py "checkpoint/Flow_Wide_ResNet50_2_V2.pt" "Wide_ResNet50_2_V2" --seed=1
python test_feature_density_estimator.py "checkpoint/Flow_Wide_ResNet50_2_V2.pt" "Wide_ResNet50_2_V2" "results/imagenet_results.csv"